tac

PROACTIVELY use when planning AI Developer Workflow execution with composable steps. Designs ADW orchestration strategies with Plan/Build/Review/Fix step composition.

PROACTIVELY use when designing agent files, system prompts, or configurations. Builds custom agent configurations for domain-specific problems using Claude Agent SDK patterns.

PROACTIVELY use when auditing or optimizing context composition. Modes - analyze (audit health, score context infrastructure), optimize (R&D framework recommendations for reduction and delegation). Specialized for context auditing and token efficiency.

PROACTIVELY use after implementation is complete to generate feature documentation. Creates concise documentation from implementation changes. Specialized for doc generation and conditional docs updates.

PROACTIVELY use when E2E tests fail. Analyzes failed E2E tests using screenshots and error context, applies fixes, and re-validates user journeys.

Guide creation of AI Developer Workflows (ADWs) that combine deterministic orchestration code with non-deterministic agents. Use when building automated development pipelines, designing AFK agent systems, or implementing the PITER framework.

Create specialized agent experts with pre-loaded domain knowledge using the Act-Learn-Reuse pattern. Use when building domain-specific agents that maintain mental models via expertise files and self-improve prompts.

Implement hooks for permission control and security in custom agents. Use when adding security controls, blocking dangerous operations, implementing audit trails, or designing permission governance.

Manage agent fleet through CRUD operations and lifecycle patterns. Use when creating, commanding, monitoring, or deleting agents in multi-agent systems, or implementing proper resource cleanup.

Guide creation of focused single-purpose agents following the One Agent One Prompt One Purpose principle. Use when designing new agents, refactoring general agents into specialists, or optimizing agent context for a single task.